Understanding and Selecting Geospatial Analytics Tools

Transcription

1 Understanding and Selecting Geospatial Analytics Tools A Practical Example COLLABORATIVE WHITEPAPER SERIES

2 Geospatial Business Intelligence (BI) has been in the conversation related to BI now for quite some time. Simply stated, it is the relating of analytical data to geography, usually through the use of visualization techniques to relate metrics to their location on a map. Being able to relate key business metrics such as sales, inventory, target customer density, and claims experience gives business insights into how best to optimize resources to address the effect of geography. As Director of Business Intelligence, I am constantly trying to keep abreast of the latest features and functions offered by the various BI vendors in the marketplace. This article describes my experiences in selecting and using software that incorporates geospatial data in the pharmaceutical industry and provides recommendations and considerations for selecting BI software for handling geospatial data. I first came across a geospatial capability that was integrated with a BI platform a few years ago, when I was researching the general capabilities offered by a leading Open Source BI vendor. This capability was in the form of an online demonstration to show how, if your data had geographic attributes, you could pass selected data from your analysis to mapping software so that you could visually see on a map of the US where certain sites were located. Seeing this type of information presented on a map as opposed to a traditional chart can lead to quicker and clearer insight about the information being shown. Where decisions that can be affected by geographic proximity are concerned, such as looking into why a customer is receiving late delivery times or looking into what customers are covered by each field sales rep, physically seeing this information on a map instead of via a chart or table of values ensures that more rapid decisions can be made. Up to 80 percent of an organization s data is geography based. Given that, it seems reasonable that geospatial analytics could be very valuable in most organizations. I. Geospatial needs A practical example of requirements My next significant encounter with geospatial analytics came when I was asked to help put together a prototype dashboard as part of a solution offering during the summer of I listed the time frame because, as everyone is aware, if there s one constant in the BI world, it s change! And the features and functions offered by BI vendors are constantly changing. The solution that the client wanted to offer was being developed to address the needs of the pharmaceutical industry and was being considered as part of a Softwareas-a-Service model. This particular solution provides a good example of how geospatial analysis can be leveraged given the broad set of requirements it needed to address. 2

3 To understand why geospatial analytics was a critical need here, you need to understand more about the type of data that is provided and bought by pharmaceutical companies. Data is purchased from most of the major pharmacies across the country, aggregated and then sold to pharmaceutical companies so that they can analyze the particular market or markets that they are in and ascertain their drugs market share in relation to the competition. Pharmaceutical companies are not interested in you as an individual, but they are interested in: The prescription drugs that are bought The Health Plan that paid for the prescriptions What purchasing priority is given to their product by the health insurance company What the co-pay was for that drug Which doctor prescribed it Where the pharmacy was located This information gives pharmaceutical companies great insight into their products acceptance in the market as it relates to doctors, health plans, and their competition. As well as the typical charts and graphs showing metrics and KPI s, the solution had several key geospatial analytic requirements (some of which were not part of the prototype, but had to be part of the chosen solution). So why were geospatial analytics needed? Traditional charts and graphs are good at relaying certain information. Consider the following typical business questions: How is brand X performing relative to brand Y? What sales territories are performing better than others? Presenting the answers to these types of questions can be easily done using traditional charts and graphs such as bar graphs or pie charts, where metrics such as revenue or margin over a given time period can be easily plotted. These types of graphics are best at relaying this information. But, for this service offering, some of the questions we were trying to help pharmaceutical companies answer were: Which doctors were prescribing the drugs in their market and who were the doctors not prescribing their drugs? Based on their sales territories, which sales reps were best placed to call on particular doctors? Which pharmacies sold what drugs? Where were they? Based on the demographics of a particular area and the average co-pays on the drug in that area, would co-pay cards lift sales? The above questions are just illustrative, to show why geospatial analysis was a key requirement of the service offering. The major requirements were: Being able to see key metrics such as Number of Scripts prescribed by a doctor for a given brand on a map. This was needed so that pharmaceutical companies could target the appropriate doctors. Typically, mapping technologies such as Google Maps show locations on maps via a marker of some description. Clearly, in this type of analysis, for a user to assimilate the information provided and draw appropriate conclusions, these key metrics needed to be represented as a visual object such as a bubble on the map, and the size or color of the bubble could be reflective of the magnitude of the value of the particular metric selected. For example, larger bubbles could reflect a greater number of scripts than a smaller bubble. Having a drill down, drill anywhere capability on the map. The solution needed to have users initially see a map of the US and based on the metric being shown, be able to highlight an area by using the mouse, and drill down and zoom to that particular area of the map. This drill down ultimately goes to a street name and/or address. Overlay on a map, sales force territory alignments. Mapping technologies typically show, for the US, States, Counties, Metropolitan Service Areas (MSA s) and zip codes. This solution needed to be able to offer clients a way to create and show their own particular sales force territories on a map so they could see which doctors were covered by particular sales reps. 3

4 Inclusion of third party data such as Census Bureau data on the map. Certain drugs may be targeted to certain age groups. By overlaying areas with color coding based on age groupings, a drug company can see whether their drugs are targeted to the appropriate areas, based on the demographics of the population in a particular area or whether co-pay cards were needed based on income distribution. This type of analysis is harder to depict using traditional charts and graphs. Another major requirement to consider that was not part of this effort is bi-directional analysis. Bi-directional analysis is the ability to go from say, a bar chart to a map and then based on the selection in the map, pass the map information back to a report. Consider the following example. Company X has a bar chart depicting sales of their products by state product Z is the worst performing product in Florida. By clicking on the bar for product Z, a map of sales of product Z in Florida is displayed. It shows sales to all customers are down within a certain area. Overlaying the distribution centers and their territories, it was found that all those customers were covered by a particular distribution center, let s say center Y. This center had low inventory due to a fire. By clicking on that center, a report of the customer s services by that center was generated. These customers could then be contacted to explain the reason for company X s poor service levels. II. Geospatial options Not just dots on a map Continuing with our example, for the prototype, the initial choice was to use an in-memory analytics vendor. The vendor had originally been chosen before any of the geospatial requirements were known and was selected because of a perceived speed of development, speed of the system, and the visual aesthetics of its graphing capabilities. Choosing a vendor before all the major requirements are known can be a big mistake, especially as geospatial analytics was seen as a key differentiator. In our case, as it was a prototype, and because a demonstration license was used, it didn t have a material effect on the outcome of the prototype. So, despite some additional risks, the initial choice lead to a more exhaustive set of criteria being developed with which to evaluate potential vendors for the actual solution. What I came to realize, by creating this prototype and by doing subsequent research on the web, was that there are not many BI vendors in the market that have integrated geospatial offerings. Most of the BI vendors in the marketplace can perform two basic types of geospatial analysis. Both of these types start off with dots on a map. 1. Show information on pre-defined, high-level, static maps such as showing North America with all states and provinces. 2. Integrate with something like Google Maps and pass, through a URL, latitude and longitude coordinates to show various points on a map. Some customization can generally be done with this integration such as when the mouse hovers over a pointer, having a chart or graph of a pie chart of additional information show up for example. However, as we discussed above, this set of capabilities only scratches the surface of a geospatial offering and definitely does not meet the needs described in the above example. For this particular prototype, we leveraged the Google Maps API along with a bubble chart that had a transparent backing, thereby giving the impression it was an integrated visualization (see Figure 1). The BI Vendor provided support for this element of the prototype as it was not a truly native feature in their product. The expressions necessary to plot the bubble chart correctly over the maps was a trigonometric piece of genius, and probably took someone from NASA s jet propulsion lab to figure it out! III. What do the major business intelligence vendors offer? Since 2009, when this dashboard prototype was put together, the number of vendors offering geospatial capabilities has increased dramatically with most of the main vendors either having their own capabilities or integrating with a third party mapping technologies. Figure 1 and Figure 2 show the contrast in mainstream geospatial capabilities, between what was available then in 2009 and now in

5 Figure 1: An example of geospatial capabilities back in 2009 Figure 2: An example of geospatial capabilities in 2014 In my original research (conducted back in 2009), I only came across two tools with an integrated geospatial capability. The geospatial capability provided by one of these vendors was a very simple, ready-to-use, out-of-thebox approach. You merely tagged one of the data elements (that say contained a zip code) as a geo coded attribute and you were ready to go. It understood zip codes as well as Metropolitan Service Areas (MSA s). It was one step further along than just integrating with a Google Maps type of technology, although there were a few valid zip codes that it did not recognize. The other vendor that also had an integrated geospatial capability, on the other hand, had two offerings. A Google maps integration capability that worked with its core reporting software, and a fully integrated ESRI mapping capability that could satisfy all of the requirements needed for the solution including being able to create user defined areas such as sales force territories, and inclusion of census bureau or third party data. In addition, bi-directional analysis could also be accommodated. Since the prototype, I recently came across the need to have geospatial analytics while I was conducting a business intelligence strategy for a specific pharmaceutical company. One of the business sponsors, a senior level executive, was asked what type of questions he was trying to answer and what data and analysis he needed to answer those questions. His reply was that he needed to: See a map of the US depicting where sales by therapeutic area were underperforming. He wanted to know why they were underperforming and was interested in overlaying other information such as age demographics. This pharmaceutical client had fast acting drugs suited to children up to the age of 18 and a slow release version of the same drug that was suited to adults. This made overlaying age distribution very important. He wanted to overlay average incomes and co-pays to see whether the introduction of co-pay cards in targeted areas could potentially lift sales of the drugs. This set of requirements clearly illustrates the need to go well beyond dots on a map, and to more advanced visualization, incorporating significant additional data elements, and showing geography, as well as specific latitude and longitude locations. Clearly, geospatial analytics can have a very important role in a company to help answer questions where traditional analytics would struggle. It is a rapidly evolving area within the BI realm. We are seeing more and more clients request this type of analytical capability in relation to understanding their business. 5

6 IV. Conclusion How to pick the right tool There are really four major steps in the process before a tool can be selected. The first, and one of the most critical steps in the process, is to collect a prioritized set of geospatial requirements from the business. As part of this process, it is crucial to understand the business value that geospatial analytics brings to the solution as this may drive a BI vendor to be selected that is not part of the standard BI stack that a particular company has. Key business requirements such as: References 1. Louella Fernandes. Putting business intelligence on the map. Quocirca. 18 October The need to overlay and show graphically custom zones or territories such as sales territories on a map The need for bi-directional analysis to go from standard BI content such as reports and dashboards to a map and back to a report The need to represent and overlay third party data such as census bureau data on a map The second step in the process is to understand the capabilities offered by any existing in-house BI tool and in addition, what third party geospatial offerings are out there in the market place that can integrate with the particular in-house BI tools utilized. The landscape is ever-changing so this analysis should be done as close to solution design time as reasonable. The third step, and probably the most difficult or controversial, is to understand the cost versus the business benefit derived and the influence of cost in the decision process. The fourth step is to create a prototype that proves out the key or critical business requirements. This ensures that any deficiencies or limitations are known before any acquisition is made. On the surface, geospatial analysis seems like a simple requirement that should be easily satisfied by many different BI tools; but as this article indicates the problem is both challenging to describe as well as solution for. If geospatial analysis is part of your BI requirement set, you really need to understand what specifically is needed so that you can make the right choice for your organization. 6

7 Collaborative Consulting is a leading information technology services firm dedicated to helping our clients achieve business advantage through the use of strategy and technology. We deliver a comprehensive set of solutions across multiple industries, with a focus on business process and program management, information management, software solutions, and software performance and quality. We also have a set of offerings specific to the life sciences and financial services industries. Our unique model offers both onsite management and IT consulting as well as U.S.-based remote solution delivery. To learn more about Collaborative, please visit our website at us at [email protected], or contact us at Copyright 2014 Collaborative Consulting, LLC. All rights reserved. This product is protected by U.S. and international copyright and intellectual property laws. WP